Tracking and identity analysis of pedestrians in a monitoring video is of great value for many application fields. For example, as for smart retail, stores hope to learn each customer's complete trajectory inside the stores, meanwhile be aware of each customer's identity attributes such as approximate age, dressing etc., as well as action behaviors such as touching which commodities in the stores. In addition, as for security surveillance, in a sensitive scene, it needs to monitor each pedestrian in the scene being monitored, to determine whether each pedestrian has actions such as abnormal behaviors etc. Therefore, it needs to locate and track exact positions of pedestrians in the scene, and it is also hoped that by tracking pedestrians, some identity attribute information and action analysis of pedestrians can be obtained.
A single-view monitoring video acquiring device used currently cannot solve this problem. For example, in the case of using a top-view camera, although there is no blocking among pedestrians and positions of pedestrians in each frame can be located very well, it is hard to see other information of each pedestrian except his/her head due to limitations of the top-view angle per se, thus it is impossible to implement analysis of identify attributions and possible actions of pedestrians. On the other hand, in the case of using an overhead-view camera, although appearance of each pedestrian can be seen to a large extent, because of blocking among pedestrians, it makes difficulties to detection and tracking of pedestrians themselves.